Jamal, Mehtab (2024) Deep Learning Applications in Medicine: Enhancing Diagnosis and Patient Outcomes. Global Journal of Universal Studies, 1 (1). pp. 31-52. ISSN 3008-0509
Full text not available from this repository.Abstract
Deep learning has transformed the modern medicine to accurately diagnose, treat patients with uniqueness, and provide better patient outcomes. With the use of big data in medicine, imaging, electronic health record and genomic data, deep learning models identify subtle features, disease progression, and aids in clinical decision-making. The uses can include medical imaging and pathology as well as predictive analytics, remote monitoring, and AI-assisted drug discovery. Although issues like data privacy, model interpretability, and algorithmic biasness persist, such new approaches as explainable AI, federated learning, and IoT integration have greater opportunities to be safe and effective to adopt. Deep learning is building a future in the field of accuracy, effectiveness, and patient-centric care.
| Item Type: | Article |
|---|---|
| Subjects: | ?? Deep learning ?? ?? Medicine ?? ?? Medical diagnosis ?? ?? personalized medicine ?? ?? Patient outcomes ?? ?? Medical imaging ?? ?? Predictive analytics ?? |
| Depositing User: | Unnamed user with email samad2nice@gmail.com |
| Date Deposited: | 11 Sep 2026 06:43 |
| Last Modified: | 11 Sep 2026 06:43 |
| URI: | https://repository.globalsciencepress.com/id/eprint/76 |
